Assets under management (AUM) in the private debt market is estimated to surge from $848 billion at end-2020 to $1.46 trillion in five years—an impressive 11.4% annual increase. This level of growth is intensifying competition, with many hedge funds launching their own private debt products. Meanwhile, investor inflows are being ever more concentrated at the largest funds and regulatory conditions continue to tighten.

As private debt AUM grows and competition intensifies, a once "old-school" market segment heavily reliant on spreadsheets and man hours is becoming more sophisticated and private debt managers are increasingly waking up to the full competitive value that technology can bring.

This theme emerged strongly in a webinar I moderated recently. Co-sponsored by IHS Markit and AltAssets, " Private Debt: Digital Transformation - Now or Never?" featured panelists Karen Simeone, Managing Director at HarbourVest Partners, a leading global alternative asset manager ($72 billion in AUM), and Niels Bodenheim, the Head of Alternative Credit at NN Investment Partners (€45 billion in private debt AUM).

The conversation explored how private debt managers leverage technology to gain an edge in an increasingly competitive market. It was an enlightening conversation that yielded a number of important takeaways.

A single source of truth supports deeper analysis

Technology will not be replacing human judgment and decision-making anytime soon (nor should we want it too). But it can be a powerful amplifier for those things, even by enabling something seemingly simple—such as a single, centralized reference point that everybody in the team can refer to.

For Simeone, this allows lines of inquiry to go a step deeper. Instead of team members looking at a piece of data and asking, "What is this?" or "Does it really say that?", they can move to the next level and ask, "What do you think about this?" They can spend their time analyzing the data rather than validating it, which is where the real value lies.

For instance, Simeone notes that in the credit space, where investors are focused on limiting the downside, data analytics can provide granular "base rates" that can be used to kick off further evaluation. The deeper you can drill down into a specific subsector, the better the quality of your analysis and decision-making, which ultimately is the source of alpha generation and returns.

Advanced integration capabilities ensure data flexibility

Today, private fund managers need far more than just core financial data. ESG data, which has yet to be standardized, and other private data sources—much of it unstructured and qualitative—also form crucial market intelligence. Then there are the increasing data demands from the fund's investors and regulators.

In this environment, fund managers need their data to be available in highly flexible formats. That flexibility—including the ability to ingest data in a variety of formats and sources as well as the availability of APIs that enable that data to flow into other systems—is more important than robust feature sets provided by the data management system itself.

The prerequisite for these capabilities is robust integration. This is something both Simeone and Bodenheim identified as a key hurdle to increased tech adoption in private debt—a lack of integration between disparate systems.

For instance, fund managers may need to exclude superfluous data from analysis, apply bespoke metrics to specific proprietary systems or reference multiple deal databases. The more flexibly they can use their data, the wider the range of solutions they can offer their clients, and the more effectively they can leverage data to support their own unique and differentiating processes.

Finding the right solution requires not just a change in technology but a change in mindset as well. Stakeholders need to look beyond the impact on their individual job function, see the bigger picture and envision how the data can support the organization as a whole.

The focus shifts from data capture to data automation

As firms collect ever increasing volumes of data, they are realizing the importance of being able to automate data capture as much as possible.

Simeone and Bodenheim agreed that automated data capture could enhance virtually every function, highlighting workstream management, document review and deal notifications. More indirectly, automation could also boost operating efficiencies by ensuring things are executed properly the first time around.

Neither sees human decision-making being supplanted by machines any time soon. But Bodenheim suggested that the next advancement in workstream automation should come from integrating client relationships—such as potential veto rights—into those streams. In other words, where else could the "automated workstream ecosystem" be expanded as technologies continue to evolve?

Both agreed that fund managers should not be in the data capture and reconciliation business and that the process of collecting statements, plugging those numbers into systems and reconciling them is not the best use of their team's time and focus. Outsourcing these functions to best-in-class software and service providers such as IHS Markit, which offer both data systems and services for their teams to leverage, can return much-needed time that these teams can reallocate to strategic, high-value activities.

Client satisfaction is at the heart of everything

Technology is a means, not an end, and for both Simeone and Bodenheim, the ultimate end is client satisfaction. The more satisfied your clients are, the more you can grow your AUM—it's that simple.

For instance, operating efficiencies reduce costs, thereby maximizing client value. Greater responsiveness is another way to enhance client satisfaction, as clients today increasingly demand a communication frequency and level of transparency more akin to the public markets.

This extends to onboarding as well. Establishing the proper workstreams makes the sensitive onboarding process smoother, enabling firms to avoid repetitive information requests and focus on the information that really matters.

The technological advantage

Technology has already become a source of differentiation among private fund managers. This will only continue as competition intensifies, regulations tighten and new technologies such as tokenization become more mainstream.

At the larger industry level, fund managers may also need to seriously consider collaborating more with each other to increase data transparency across the board. The private nature of the industry—and the fact that data can be a competitive advantage—makes it difficult to obtain macro industry-level data. But for the industry to evolve as a whole, that may be the next necessary step forward.

Posted 01 June 2021 by Jocelyn Lewis, Vice President, Head of Commercial Strategy for Private Debt Software Solutions, Americas, S&P Global Market Intelligence

S&P Global provides industry-leading data, software and technology platforms and managed services to tackle some of the most difficult challenges in financial markets. We help our customers better understand complicated markets, reduce risk, operate more efficiently and comply with financial regulation.

This article was published by S&P Global Market Intelligence and not by S&P Global Ratings, which is a separately managed division of S&P Global.